Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Clainche, Soledad Le"'
The proliferation of unmanned aerial vehicles (UAVs) in controlled airspace presents significant risks, including potential collisions, disruptions to air traffic, and security threats. Ensuring the safe and efficient operation of airspace, particula
Externí odkaz:
http://arxiv.org/abs/2407.06909
Autor:
Bell-Navas, Andrés, Groun, Nourelhouda, Villalba-Orero, María, Lara-Pezzi, Enrique, Garicano-Mena, Jesús, Clainche, Soledad Le
Heart diseases are the main international cause of human defunction. According to the WHO, nearly 18 million people decease each year because of heart diseases. Also considering the increase of medical data, much pressure is put on the health industr
Externí odkaz:
http://arxiv.org/abs/2404.19579
Fluid dynamics problems are characterized by being multidimensional and nonlinear, causing the experiments and numerical simulations being complex, time-consuming and monetarily expensive. In this sense, there is a need to find new ways to obtain dat
Externí odkaz:
http://arxiv.org/abs/2404.17884
This paper presents a new method capable of reconstructing datasets with great precision and very low computational cost using a novel variant of the singular value decomposition (SVD) algorithm that has been named low-cost SVD (lcSVD). This algorith
Externí odkaz:
http://arxiv.org/abs/2311.09791
The chaotic flow of elastic fluids at low Reynolds number (Re) is typically distinguished into elasto-inertial and elastic turbulence (EIT/ET). However, the clear separation among these two turbulent regimes in parallel flows with a gradual Re decrea
Externí odkaz:
http://arxiv.org/abs/2310.05340
Fluid Dynamics problems are characterized by being multidimensional and nonlinear. Therefore, experiments and numerical simulations are complex and time-consuming. Motivated by this, the need arises to find new techniques to obtain data in a simpler
Externí odkaz:
http://arxiv.org/abs/2305.08832
In this work, a new hybrid predictive Reduced Order Model (ROM) is proposed to solve reacting flow problems. This algorithm is based on a dimensionality reduction using Proper Orthogonal Decomposition (POD) combined with deep learning architectures.
Externí odkaz:
http://arxiv.org/abs/2301.09860
In this work, a new algorithm based on the application of higher-order dynamic mode decomposition (HODMD) is proposed for feature selection and variables clustering in reacting flow simulations. The hierarchical HODMD (h-HODMD) performs a reduction o
Externí odkaz:
http://arxiv.org/abs/2301.07976
Autor:
Corrochano, Adrián, Sierra-Ausín, Javier, Martin, Juan Ángel, Fabre, David, Clainche, Soledad Le
In this article, a thorough characterization of the configuration composed by two concentric jets at a low Reynolds number is presented. The analysis comprises a layout with a wide range for the velocity ratio between the inner and outer jets, define
Externí odkaz:
http://arxiv.org/abs/2301.04429
Autor:
Mata, León, Abadía-Heredia, Rodrigo, Lopez-Martin, Manuel, Pérez, José M., Clainche, Soledad Le
This work aims to improve fuel chamber injectors' performance in turbofan engines, thus implying improved performance and reduction of pollutants. This requires the development of models that allow real-time prediction and improvement of the fuel/air
Externí odkaz:
http://arxiv.org/abs/2212.12731